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20072026
most citedSciPy 1.0--Fundamental Algorithms for Scientific Computing in Python

40.2k citations

Showing 2017Show all

6 papers · 1 filter

stat.ME2017★ 6 cited

Adaptive Designs for Optimal Observed Fisher Information

Adam Lane

Expected Fisher information can be found a priori and as a result its inverse is the primary variance approximation used in the design of experiments. This is in contrast to the co…

stat.ML2017

Clonal analysis of newborn hippocampal dentate granule cell proliferation and development in temporal lobe epilepsy

Shatrunjai P. Singh, Candi L. LaSarge, Amen An +2

Hippocampal dentate granule cells are among the few neuronal cell types generated throughout adult life in mammals. In the normal brain, new granule cells are generated from progen…

stat.AP2017★ 4 cited

Bayesian Nonparametric Inference for Panel Count Data with an Informative Observation Process

Ye Liang, Yang Li, Bin Zhang

In this paper, the panel count data analysis for recurrent events is considered. Such analysis is useful for studying tumor or infection recurrences in both clinical trial and obse…

cs.LG2017★ 674 cited

Distance and Similarity Measures Effect on the Performance of K-Nearest Neighbor Classifier -- A Review

V. B. Surya Prasath, Haneen Arafat Abu Alfeilat, Ahmad B. A. Hassanat +4

The K-nearest neighbor (KNN) classifier is one of the simplest and most common classifiers, yet its performance competes with the most complex classifiers in the literature. The co…

astro-ph.GA2017★ 34 cited

The role of the most luminous, obscured AGN in galaxy assembly at z~2

Duncan Farrah, Sara Petty, Brian Connolly +14

We present HST WFC3 F160W imaging and infrared spectral energy distributions for twelve extremely luminous, obscured AGN at , selected via "Hot, Dust Obscured" mid-infra…

stat.ML2017★ 5 cited

A Comparison of Resampling and Recursive Partitioning Methods in Random Forest for Estimating the Asymptotic Variance Using the Infinitesimal Jackknife

Cole Brokamp, MB Rao, Patrick Ryan +1

The infinitesimal jackknife (IJ) has recently been applied to the random forest to estimate its prediction variance. These theorems were verified under a traditional random forest…